Systems and methods for unmanned vehicle management

ABSTRACT

This disclosure relates to gathering, storing, analyzing and distributing data acquired by unmanned vehicles after catastrophes. The vehicles can be terrestrial, aerial, nautical, or multi-mode. The gathering phase of the process may being by receiving requests from the interested consumers as to the type of information desired, and this information is used to determine and/or configure the mission. The storage phase may include pre-processing data during the mission, and optionally storing the data in a cloud network. The analysis phase may be performed vehicle-side, server-side, or a combination thereof.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Appl. No.62/058,990, filed Oct. 2, 2014, and U.S. Provisional Appl. No.62/108,137, filed Jan. 27, 2015, and U.S. Provisional Appl. No.62/140,107, filed Mar. 30, 2015, and U.S. Provisional Appl. No.62/148,823, filed Apr. 17, 2015, the contents of each of which areincorporated herein in their entirety.

BACKGROUND

When a customer of an insurance company needs to exercise a claim intheir policy, anything the insurance company can do to accelerate thecustomer's reimbursement helps not only the customer but also theinsurance company in terms of closing matters as quickly as possible.This can be particularly important after natural disasters, such as ahurricane or earthquake, which may impact a high number of the insurancecompany's customers.

This disclosure relates at least in part to identifying how unmannedvehicles can operate in restricted areas, and this disclosure alsorelated to facilitating claims processing, and in particular,facilitating claims processing that utilizes unmanned resources, such asunmanned vehicles.

SUMMARY

Disclosed herein is process of unmanned vehicle management. For example,management by unmanned vehicles after catastrophes or events causingwidespread damage to support an insurance claims process or other entityprocesses. Described herein are systems and methods for facilitatingclaims processing, such as by utilizing unmanned vehicles. The vehiclescan be terrestrial, aerial, nautical, or multi-mode. They can beremotely piloted, operate with an autopilot, or a combination of both.This process may serve the diverse data needs of multiple entities, withonly a single entity engaged in the execution of the mission. This is sothat coordination can be centralized, the safety of other operations,people and property can be maximized, and the effort to gain authorityto operate is streamlined.

In one exemplary use, the gathering phase of the process begins byreceiving requests from the interested consumers as to the type ofinformation desired (e.g., type of sensor data, acquisition frequency,area of interest, etc.). This information is used in the process step todetermine the necessary mission to satisfy the consumers. The prioritiesof the vehicle deployments are ranked based on the value attributed tothe mission. Deployments are coordinated with the governing entity andexecuted to collect the data. During the gathering phase the originalmission may be modified based on new inputs from customer's, or based onanalysis of the data conducted during the mission that indicates thecurrent or subsequent vehicle deployments can be altered to moreeffectively and efficiently complete the mission.

Described herein are systems and methods for facilitating claimsprocessing, such as by utilizing unmanned vehicles. In one aspect,unmanned aerial surveillance (UAS), such as an unmanned aerial vehicle,is utilized to gather data related to one or more insurance claims. TheUAS may be sent on a mission to gather data over an area that hasrecently been subject to an event that caused widespread damage (e.g.,hurricane). The UAS may process the data internally before forwardingthe data to a central server, and the data may be forwarded during themission, and/or after the mission is complete. The data from the UAS maybe shared between multiple entities and utilized to initiate and/oraccelerate processing of claims against insurance policies.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter. Furthermore, the claimed subject matter is not limited toimplementations that solve any or all disadvantages noted in any part ofthis disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

So that those having ordinary skill in the art, to which the presentinvention pertains, will more readily understand how to employ the novelsystem and methods of the present invention, certain illustratedembodiments thereof will be described in detail herein-below withreference to the drawings, wherein:

FIG. 1 is a flowchart depicting illustrative operation of one or moreembodiments described herein;

FIG. 2 depicts one embodiment of a system that may practice thisdisclosure;

FIG. 3 is a flowchart depicting illustrative operation of the system ofFIG. 2;

FIG. 4 is an exemplary computing device that may be utilized to practiceone or more aspects of this disclosure;

FIG. 5 is another flowchart depicting another illustrative operation ofthe system of FIG. 2; and

FIG. 6 is a third flowchart depicting yet another illustrative operationof the system of FIG. 2;

FIG. 7A illustrates an exemplary overview of the step gathering(collecting) phase and the distribution step;

FIG. 7B illustrates an exemplary detailed data collection process ofFIG. 7A;

FIG. 7C illustrates an exemplary flight planning process of FIG. 7A;

FIG. 7D illustrates an exemplary customer data notification process ofFIG. 7A;

FIG. 7E illustrates an exemplary customer data authentication andretrieval process of FIG. 7A; and

FIG. 8 illustrates an exemplary aspect of the gathering, storing, andmission modification process.

A component or a feature that is common to more than one drawing isindicated with the same reference number in each of the drawings.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The present disclosure is directed to claims processing, such as may befacilitated by utilizing unmanned aerial surveillance. It is to beappreciated that this disclosure is described below more fully withreference to the accompanying drawings, in which illustrated embodimentsare shown. The present disclosure is not limited in any way to theillustrated embodiments as the illustrated embodiments described beloware merely exemplary of the disclosure, which can be embodied in variousforms, as appreciated by one skilled in the art. Therefore, it is to beunderstood that any structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative for teaching one skilled in the art tovariously employ the present disclosure. Furthermore, the terms andphrases used herein are not intended to be limiting but rather toprovide an understandable description of the invention.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present disclosure, exemplarymethods and materials are now described.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an,” and “the” include plural referents unless thecontext clearly dictates otherwise. Thus, for example, reference to “astimulus” includes a plurality of such stimuli and reference to “thesignal” includes reference to one or more signals and equivalentsthereof as known to those skilled in the art, and so forth.

It is to be appreciated that certain embodiments of this invention asdiscussed below are a software algorithm, program or code residing oncomputer useable medium having control logic for enabling execution on amachine having a computer processor. The machine typically includesmemory storage configured to provide output from execution of thecomputer algorithm or program. As used herein, the term “software” ismeant to be synonymous with any code or program that can be in aprocessor of a host computer, regardless of whether the implementationis in hardware, firmware or as a software computer product available ona disc, a memory storage device, or for download from a remote machine.The embodiments described herein include such software to implement theequations, relationships and algorithms described above. One skilled inthe art will appreciate further features and advantages of the inventionbased on the above-described embodiments. Accordingly, the disclosure isnot to be limited by what has been particularly shown and described,except as indicated by the appended claims. Further, although at leastone series of steps are presented as an exemplary method of practicingone or more embodiments described herein, it will be appreciated bythose skilled in the art that the steps identified may be practiced inany order that is practicable, including without limitation the omissionof one or more steps.

A First Contemplated Embodiment and/or Use Case:

Turning now to FIG. 1, illustrated therein is a process 10, for usingone or more embodiments described herein. Starting at step 11, a vehicleis deployed to a property. This deployment may be in response to anotification that the property has been damaged (e.g., the propertyowner contacted his/her insurance company), or this deployment may be inresponse to an event that caused damage in and around the property(e.g., a nearby tornado), and/or this deployment may be simply aperiodic deployment to gather additional information.

Next, at step 12, an encryption key may be received, such as at thevehicle, and the encryption key may be utilized to encrypt at least someof the data gathered about the property, and at step 13, data about theproperty may be gathered and optionally encrypted. For example, usingthe private key/public key encryption system exemplified by the RSAalgorithm, either the public key or the private key (preferably,although not necessarily, the public key) may be sent to the vehicle. Inresponse, as the vehicle gathers data that pertains to the property(e.g., an image that at least partly includes the property), the vehiclemay encrypt that data. It is contemplated herein that the entire data(e.g., the entire image) may be encrypted as a result of the propertybeing included in the data (e.g., image), and it is also contemplatedherein that only the part of the data (e.g., image) that includes theproperty may be encrypted (e.g., the parts of the data not related tothe property may be cropped out of the data, thus leaving onlyproperty-related data to be encrypted).

Next, at step 14, previously gathered data (e.g., from a previousday/week/month/year) may optionally be compared to real-time gathereddata. This comparison may enable the identification of a part of astructure that may be left. For example, if the real-time imagediscloses some rubble and/or one or more walls of a structure, thecomparison to the previously-gathered image may reveal that thestructure at that location has been partially and/or (almost) completelydestroyed.

Subsequently, communications between the vehicle and a smart home systemmay be executed (step 15). It is contemplated herein that the smart homesystem may be any type of electronic-based system that is involved withmanaging/monitoring/controlling a property. For example, a smart homesystem may be any system that monitors what appliances are beingoperated, what the conditions are (what rooms have movement, whattemperature each room is), and/or actually controls aspects of thestructure (e.g., if no one is home, reset the thermostat to atemperature that is less expensive to maintain). Further, although theterminology “smart home” is used within this paragraph and disclosure,it is contemplated herein that the property/structure management systemmay be for any residential, commercial, and/or industrial property aswould be recognized by those skilled in the art.

Finally, data may be communicated back to a (central) server (step 16)and/or a cloud service. For example, the vehicle may communicate via itsown communication means (e.g., via a satellite link) back to the server.In another example, the vehicle may leverage a communication link with asmart home to send data to a server (e.g., the vehicle may send the datato the smart home, and the smart home could utilize its owncommunication means (e.g., its own ISP (Internet Service Provider)) toforward the data along).

It is contemplated herein that the data gathered about the property maybe any data as described herein, and gathered from any of the sensorsthat are also described and referenced herein. Further, the vehicle maybe enabled with functionality to analyze gathered data (e.g., an image)and determined whether the image sufficiently contains what is needed.For example, if the vehicle has been tasked with identifying the statusof a residential home, and the vehicle gathers a visual image of thehome from a relatively large distance (e.g., 1,000 feet), the image maybe analyzed to determine that a closer and/or more zoomed-in image isneeded to enable the functionality and analysis related to identifyingwhat damage, if any, has occurred to the home.

Further, after the data is gathered, that data may be encrypted, stored,and/or shared according to various criteria. In one example, the vehiclemay be deployed and instructed to gather information about a pluralityof homes that are insured by three companies: Company A, Company B, andCompany C. In this example, each of those companies may purchase and/orbe entitled to certain services related to the vehicle's operation. Forexemplary purposes only and without limitation, they may purchase anamount of data to be gathered and analyzed by the vehicle, they maypurchase an amount of storage space that the data relating to thecompany's properties may be stored in, and/or they may purchase anamount of communication bandwidth that the data relating to thecompany's properties may be communicated over. With respect to that lastexample, it is contemplated herein that the purchased bandwidth mayrelate to a total amount of data to be communicated (e.g., a total of 10GB), an amount of real-time bandwidth (e.g., 5 Mb/second (this exampleis of five mega-bits (hence the lower-case “b”) per second)), a totalamount of data bandwidth per communication means (e.g., 2 GB persatellite link, 1 GB per smart home network daisy-chaining), an amountof real-time bandwidth per communication means (e.g., 1 Mb/second for asatellite link, 0.25 Mb/second for smart home network daisy-chaining),and/or any other communication limitations and management as may becontemplated by those skilled in the art.

Continuing with these examples with respect to purchased data storagespace and/or purchased bandwidth, it is contemplated herein thatgathered and/or encrypted data may be deleted if the availablestorage/communication means is insufficient (e.g., if there is nostorage space left and/or there is a reduced amount of storage space,then that the remaining space cannot be allocated for the image based onthe image's calculated expected value to the company as compared to theamount of storage/communication bandwidth left (e.g., if the image isonly kind of valuable and revealing about the conditions of theproperty, and the limited amount of storage space/bandwidth isinsufficient to justify keeping an image of such limited value)).

In another example, the vehicle could communicate with a computingdevice that manages, at least in part, a structure on the property(e.g., a smart home). It is contemplated herein that the communicationmeans may be via Wifi, Bluetooth, radio frequency, and/or any means aswould be known and recognized by those skilled in the art. Continuing inpart with the example above where three companies have tasked thevehicle to collect information about properties that the companiesinsure, for this example the vehicle may be communicating with a smarthome that is insured by Company A.

It is contemplated herein that Company A may enable communicationsbetween the smart home and the vehicle by communicating to each thatCompany A authorized those two devices to communicate (secure)information. For example, Company A may supply the vehicle with apassword/PIN that the vehicle can supply to the smart home to tell thesmart home that the vehicle is authorized to learn about the smart home,and optionally even instruct the smart home to perform certain actions(e.g., change the thermostat, turn off the water/gas). In anotherexample, Company A may communicate to the smart home (e.g., via thehome's ISP) that the vehicle (which may be uniquely identified) is senton Company A's request, and therefore the smart home should communicate(fully) with it.

In another example, particularly sensitive data (e.g., an access code toa home's security system) may not be communicated, such as to a cloudcomputing data storage facility, and instead the data may be kept on thevehicle and only a reference to the sensitive data may be communicatedand externally stored. Thus, this information has a reducedaccessibility to potential hackers.

In another example, the vehicle may analyze data about a property (e.g.,an image) to determine that additional data may be required. As aresult, the vehicle may instruct and/or request a second vehicle togather the additional data. It is contemplated herein that theinstruction/request may be communicated directly from the first vehicleto the second vehicle, and/or it may be via the first vehiclecommunicating that additional data is needed, and that request beingforwarded to a second vehicle that has been identified as a result ofthe need for additional data.

In another example, the vehicle may identify a problem and instruct thesmart home to address that problem. For example, the vehicle mayidentify that gas is leaking (e.g., via visual detection of a problemwith a pipe, via detecting the gas in the air), and instruct a smarthome to shut off (e.g., an emergency shut off) the gas. Further, it iscontemplated herein that this may also be applied to leaking waterand/or any other problem that the smart home may be leveraged tomitigate the possibility of additional damage being caused because ofthat.

In one embodiment, a third party operates, manages, and/or controlsunmanned vehicle 100 and/or server 150, and distributes the datagenerated and developed therefrom to the one or more providers 160 thatare associated with the property to which the data and/or the subset(s)of the data relate.

In another embodiment, providers 160 gather data and send the data to apool, from which the data is culled and distributed to the one or moreproviders to whom the distributed data is pertinent and/or relates. Theproviders 160 may need to authenticate that they have a policy thatcovers the item to which the data relates, and/or the providers 160 mayneed to authenticate that the location (e.g., GPS) of the item (e.g.,home) about which they are requesting information.

In another embodiment, determination of which providers 160 are allowedto deploy vehicles 100 to an area may be at least partially based on theamount of area about which information needs to be gathered.

In another embodiment, a first set of data is gathered (e.g., zoomed outoptical imagery), and from that data it is analyzed and determined apriority of what property needs more data gathered therefrom (e.g., ifdamage is still occurring to a property (e.g., an active fire burning apart of the house) then gathering more data about the property's instantdamage state may prove useless as the property will likely end up beingadditionally damaged, and thus, said property should be a low priorityabout gathering additional data at this time).

In another embodiment, tiers of data are collected, such as, forexemplary purposes only and without limitation, visual light imagerydata, hyperspectral imagery data, infrared data. Said tiers may behandled, distributed, and/or analyzed alone or in combination.

In another embodiment, unmanned vehicle 100 may take imagery that isanalyzed to determine if a house has sustained structural and/or roofdamage. For example, the engines on unmanned vehicle 100 and/or engineson server 150 may analyze the data (e.g., imagery) to determine if aroof at a certain coordinate has all of the corners and edges andwhether said corners and edges of said roof appear to be damaged. Inanother example, the engines on unmanned vehicle 100 and/or engines onserver 150 may analyze the data (e.g., imagery) to determine the extentof damage that has occurred (e.g., the percentage of damage to acomponent (e.g., roof) of a home, the percentage of damage to an insuredentity (e.g., a home), the percentage of damage to an area of homes). Inthis and/or other examples, the engines on unmanned vehicle 100 and/orengines on server 150 may determine and identify which item or items ina home are damaged (e.g., roof, walls, windows, porch).

In another embodiment, unmanned vehicle 100 is deployed with datarelevant to its mission (e.g., here is imagery from before the disaster,here are the coordinates of insured's property), and such data may beutilized by unmanned vehicle 100 to determine how to manage and/or alterthe mission.

In yet another embodiment, data gathered by unmanned vehicle 100 may becompared and/or utilized in coordination with data gathered from othersources. For example, data may be utilized that is gathered from a“smart building” (a building, residential, commercial and/orindustrial), such as via one or more sensors deployed on and/or near thesmart building.

In another embodiment, sensors 145 are utilized to detect if electricallines are hot (e.g., temperature-wise and/or by virtue of currencypassing through them) and/or if there is a leak of a dangerous substance(e.g., natural gas).

One or More Other Contemplated Embodiments and/or Use Cases:

Referring to FIG. 2, disclosed therein is a system 90 in which theprocesses described herein may be executed. In one example, system 90may include unmanned system 100, vehicle 110, data analysis engine 120,route determination engine 130 and sensor management engine 140. System90 also includes network 50, communications 75, server 150, and provider160, the last two of which are communicably connected.

Referring further to FIG. 2, it is to be appreciated that network 50depicted in FIG. 2 may include a local area network (LAN), a wide areanetwork (WAN), a personal area network (PAN), and/or combinationsthereof. Such networking environments are commonplace in offices,enterprise-wide computer networks, intranets, and the Internet. Forinstance, when used in a LAN networking environment, system 90 isconnected to the LAN through a network interface or adapter (not shown).When used in a WAN networking environment, the computing systemenvironment typically includes a modem or other means for establishingcommunications over the WAN, such as the Internet. The modem, which maybe internal or external, may be connected to a system bus via a userinput interface, or via another appropriate mechanism. In a networkedenvironment, program modules depicted relative to system 90, or portionsthereof, may be stored in a remote memory storage device such as storagemedium. Computing devices may communicate over network 50 through one ormore communications links 75 formed between data interfaces.Communication links 75 may comprise either wired or wireless links. Itis to be appreciated that the illustrated network connections of FIG. 2are exemplary and other means of establishing a communications linkbetween multiple devices may be used.

Still referring to FIG. 2, data analysis engine 120 is utilized toreceive, store, and analyze data retrieved by the one or more sensors145 on unmanned system 100. Such analysis may include comparing imagerydata to stored coordinates to identify additional and/or replacementimagery that may need to be gathered.

Route determination engine 130 is utilized to manage unmanned system 100and confirm that unmanned system 100 remains on a planned mission path.Route determination engine 130 may also determine, based on gathereddata and the results of data analysis engine 120 processing said data,modifications to the route of unmanned system 100. For example, iffurther imagery is needed of a certain location, or if imagery is neededfrom a different perspective and/or angle, route determination engine130 may control and/or inform unmanned system 100 to vary the missionpath accordingly.

Sensor management engine 140 controls the one or more sensors 145installed on unmanned system 100. This control may include determiningwhich sensors 145 are gathering data, the operating characteristics ofsaid data gathering (e.g., the level of zoom of a visible light camera),where sensors 145 are aimed, and/or any other sensor performance controlvariables as would be recognized by those skilled in the art.

It is contemplated herein that sensors 145 may include a visible lightcamera, an infrared camera, a microphone to detect sound, a particleinspection device (e.g., a device that can detect what compounds are insampled air gathered by unmanned system 100), radar emitting/detectingdevice(s), a spectrometer, a hyperspectral sensor, and/or any othersensors as would be recognized by those skilled in the art.

Referring to FIG. 3, exemplary operation of a process 200 of unmannedsystem 100 will now be described for illustrative purposes.

Starting at step 201, information is gathered that indicates that amission should be generated. Such information may include, for exemplarypurposes only and without limitation, that a local disaster has occurred(e.g., a tree fell on the house that is owned by someone with aninsurance policy with provider 160), that a medium-scale disaster hasoccurred (e.g., a fire that spread between several houses on a street,of which one or more of the houses may be insured, but are notnecessarily insured, by provider 160), a wide-spread disaster willand/or may occur soon (e.g., a hurricane is forecast to hit an area, aforest fire may engulf an area, an earthquake is about to occur, avolcano is about to erupt), a wide-spread disaster is occurring (e.g., ahurricane is over an area of interest to provider 160, an earthquake iscurrently occurring, a volcano is currently erupting, a fire, be itforest or other, is currently damaging/destroying one or more homes),and/or a wide-spread disaster has occurred (e.g., any of the eventsdescribed herein).

Generally speaking, the event identified by the information relates todamage that may occur to one or more homes insured by provider 160.However, it is contemplated herein that the event may be unrelated tohomes and/or property (real or personal) that is insured by provider160.

Subsequently, a mission is generated to gather data (step 202). Thismission may include deploying (step 203) an unmanned aerial vehicle(e.g., vehicle 110), a manned aerial vehicle, and/or any vehicle, be itmanned, unmanned, aerial, ground-based, or otherwise. It is furthercontemplated herein that the mission may include identifying any otherdevices (e.g., satellite) that may be utilized to gather the requireddata. Although unmanned vehicle 100 is, as the name suggests, unmanned,it is contemplated herein any mechanical device may be deployed andutilized to practice the systems and methods disclosed and describedherein. Further, it is also contemplated herein that a sensor 145, suchas a non-moving sensor 145 or sensors 145, may be placed at or near thescene where a disaster has occurred and/or is expected to occur. Forexample, the sensor 145 may be placed on or near an expected path for ahurricane. The placement may be via a drop, an attachment to a buildingand/or structure (artificial and/or natural), or any placement as wouldbe recognized by those skilled in the art.

Data is gathered via the one or more sensors 145 on unmanned system 100(step 204). This data may be gathered by aiming sensors 145 (e.g.,cameras for visible light, cameras for other wave lengths), adjusting azoom factor for sensors 145 (e.g., zooming the camera(s) in or out),coordinating an amount of time to gather data (e.g., continuously fordigital imagery, length of exposure for still imagery, amount of air tobe gathered to be tested according to a particulate sensor 145), and/orother sensor controlling means as would be recognized by those skilledin the art.

The data is then analyzed, such as by comparing the imagery to a mapgrid stored in unmanned vehicle 100, mapping the imagery to the mapgrid, determining that additional imagery is needed (e.g., a moredetailed image and/or video), and indicating to unmanned vehicle 100that said additional imagery is needed. It is contemplated herein thatsaid analysis may be conducted via one or more engines on unmannedvehicle 100, via server 150 on the ground, via server 150 located inanother vehicle (be it unmanned, manned, aerial, or grounded), and/or acombination thereof. Thus, it is contemplated herein that, whiledeployed, unmanned vehicle 100 may be in communication with server viaradio waves, via satellite communications, via WiFi, any othercommunications now known or to be developed, and/or any combinationthereof.

In one embodiment, providers may pay a fee for analysis of propertiesinsured by providers to be analyzed on unmanned vehicle 100 rather thanhaving to be analyzed via the ground systems. Not only would this allowfor faster processing and utilization of the resultant analysis, but ifnetwork connectivity to the ground is absent and/or inconsistent, thiswould allow for the provider to position unmanned vehicle 100 to gathermore useful information for the provider's properties. In anotherembodiment, the flight path and/or the prioritization of what propertiesto image and/or process may be based on what type of disaster hasoccurred. Via step 206, the existing mission may be modified and/or anew mission may be generated and executed. This decision may be based ondata that is being gathered (and the analysis thereof), new commandsand/or requests sent to the vehicle 110, and/or combinations thereof.Alternatively, and/or in combination with analysis of the data, the datamay be returned to server 150 (step 207).

Turning now to FIG. 5, illustrated therein is an exemplary method 400 ofstoring, retrieving, and distributing data. Starting at step 401, data,such as imagery data, is received. The data may have been generated byone or more sensor 145, and in one or more embodiments the data isstored with metadata that identifies what type of sensor gathered thedata, the location (e.g., via GPS) of the vehicle that gathered thedata, the location (e.g., via GPS and calculations dependent therefrom)of one or more objects in the image, and/or the day/time the data wasgathered, stored, analyzed, and/or retrieved. Subsequently, the data(and metadata) is stored (step 402). For example, every quantum of data(e.g., every pixel) may have a location (e.g., a geographical location)associated with it.

At some point, an entity (e.g., an insurance company) suppliesinformation that represents an amount of proof that the entity has legalrights to view/utilize at least a subset of the data (step 403). In FIG.5, that step is represented as occurring after the data is stored, butit is contemplated herein that this step, and indeed any step in theexemplary methods described herein, may be practiced in any practicableorder of steps as would be recognized by those skilled in the art.

Next, a request for data is received from the entity (step 404). Thestep preferably includes at least some information identifying whichdata is being requested (e.g., the identifying information islocation-centric). In response to receiving the request, responsive datais identified (step 405). The responsive data preferably is consistentwith the request (e.g., the responsive data is from the locationrequested) and it is also confirmed that the requesting entity has legalrights to view/utilize the responsive data. For example, it iscontemplated herein that the request may be for more data than theentity has yet proven they have a right to, so the responsive dataidentified and sent (step 406) is only the responsive data that theentity has a right to.

Turning now to FIG. 6, illustrated therein is an exemplary method(process 500) of at least part of the data processing described herein.Starting at step 501, data is gathered, and subsequently data mayoptionally be organized into a first group of tiers (step 502). However,it is contemplated herein that step 502 may not precede step 503 (i.e.,because step 502 is prefaced by “optionally”). Via step 503, at leastpart of the gathered data, if not all of the gathered data, is analyzed.The selection of which data is to be analyzed, to the extent that only asubset of the data is analyzed, may be based at least in part on whattier that data is in and/or whether the data is associated with aspecific entity (e.g., the data represents an object that may be insuredby an entity insurance company). After this analysis, the data mayoptionally be tiered again (step 504), and finally the data may beanalyzed again based on the tiering, and/or the data may be communicatedto a party (e.g., the aforementioned “entity”). It is contemplatedherein that the tiering of the data may result in varied analysis (e.g.,different type of analysis, different level of detail for the analysis,different priority (e.g., timing) of the analysis). It is contemplatedherein that the analysis may include converting imagery data into atextual representation of at least some of that data, detecting whetherpower lines are active (e.g., via thermal imaging, via magnetic fielddetection), whether a gas line is broken (e.g., via thermal imaging todetect a leaking gas of a different temperature than the background, viaanalysis of the gas(ses) in the air), and such analysis may be utilizedto predict (and send appropriate warnings) regarding possible futuredamages and/or accidents that may be caused by one or more of theseconditions.

In one embodiment, a buffer zone is established to keep unmanned vehicle100 away from identified locations. Such locations may be homes ofinsured properties covered by provider 160, anyone's home, people and/orgroups of people that may have been identified in the imagery, treesand/or other physical impediments, and/or smoke and/or other possibledangerous and/or interfering conditions. The buffer zone distance may bea predetermined distance that is set before the mission is generated,when the mission is generated, communicated to unmanned vehicle 100during the mission, and/or generated by unmanned vehicle 100 in responseto data analysis performed during the mission.

In another embodiment, unmanned vehicle 100 is deployed before an eventoccurs, such as a widespread disaster, in order to facilitateidentification of what damage has been caused by the event and whatdamage was pre-existing.

In another embodiment, unmanned vehicle 100 sends data to server 150 andserver 150 deletes sensitive data (e.g., imagery of people). It isfurther contemplated herein that server 150 may act in coordination witha plurality of providers 160, and server 150 may forward on to eachprovider 160 data that is pertinent and/or related to an insurance claimthat has been or may be made against a policy associated with thatprovider. In this exemplary embodiment, a single entity (e.g., a neutralparty and/or a government affiliated party) organizes and/or is involvedin the deployment of a vehicle 110, and insurance provides interact withthat single entity to obtain their information (to which they areentitled).

For example, unmanned vehicle 100 may take images of individual piecesof property (either real property or personal property), and theindividual images may be sent to the provider that has an insurancepolicy covering that piece of property (and where no provider coversthat property, said image may be deleted). In another example, unmannedvehicle 100 may take an image that includes multiple pieces of property(be it real and/or personal property). This imagery may be sub-dividedinto sub-components, each of which are exclusive either to (1) a singleprovider (e.g., the image may include a plurality of property items buteach of which is associated with the same provider, and/or (2) a singlepiece of property, either in whole or in part (i.e., in this example,the image may be entirely of a single property item or it may be aportion of the single property item).

In another embodiment, unmanned vehicle 100 uploads data instantaneously(or nearly so).

In another embodiment, unmanned vehicle 100 analyzes all and/or some ofthe data before uploading it to server 150.

In another embodiment, unmanned vehicle 100 is equipped with a possiblesurplus of sensors 145, of which only some of which may be utilized on agiven mission. In another embodiment, unmanned vehicle 100 isdynamically equipped with sensors 145 based on the parameters of themission. In another embodiment and/or use case, the types of sensors 145selected are determined at least partially based on the type of eventthat has occurred (e.g., if the event is a flood from a river, thensensors 145 that gather hyperspectral imagery may not be included onvehicle 100).

In another embodiment, data is streamed via LTE, wife, and/or anynetworking means as would be recognized by those skilled in the art. Inanother embodiment, data is streamed via one or more unmanned vehicles100 communicating and/or relaying information to a communication stationfor one another.

In another embodiment, a plurality of unmanned vehicles 100 may beassigned to a single airspace that is related to and/or is over the siteof an event such as a widespread disaster.

In another embodiment, a plurality of unmanned vehicles 100 are assignedto a plurality of airspaces that may be assigned, and said airspaces maybe exclusive of each other (or they may not be exclusive of each other).It is contemplated herein that airspaces may be exclusive of each othervia geographical coordinates (e.g., the x-axis and/or the y-axis) and/orvia altitude (e.g., the z-axis).

In another embodiment, the engines related to specific flight and safetycontrol of unmanned vehicle 100 are separate from the engines thatanalyze the data (e.g., data analysis engine 120, route determinationengine 130, sensor management engine 140).

In another embodiment, unmanned vehicle 100 may receive a request fordata, and unmanned vehicle 100 may alter a flight path to gather therequested data, optionally confirm the gathered data matches therequirements of the request, and then communicate the requested data(such as to the requesting party).

In another embodiment, hyperspectral imagery is taken, utilized, andanalyzed to determine information such as what kind of damage wassustained. For example, the engines on unmanned vehicle 100 and/orengines on server 150 may determine whether water damage was caused bysalt water or fresh water (such may be utilized to determine if aninsurance claim is characterized as flood or storm damage), and/or theextent of damage to a roof and/or a structure.

In another embodiment, a mission by an initial unmanned vehicle 100 maybe utilized to dictate and/or inform what sensor(s) 145 should beinstalled on one or more (other) unmanned vehicles 100 for futuremissions.

In another embodiment, there is an order of deployment for unmannedvehicles 100, such as, first fixed wing craft, then multi-rotor orperson or ground vehicle(s).

In another embodiment, unmanned vehicle 100 determines and relays and/orsaves the location of other unmanned vehicles 100.

In another embodiment, a request is pushed to an insured to askpermission for unmanned vehicle 100 to deploy at or near property ownedby the insured so as to enable and/or facilitate unmanned vehicle 100gathering data about the insured's property.

In another embodiment, unmanned vehicle 100 includes artificialintelligence (AI) that performs risk analysis and which is utilized toinform and/or dictate the mission path of unmanned vehicle 100.

In another embodiment, unmanned vehicle 100 may be utilized to monitoran insured's property, such as after an insured's property (e.g., car)has been stolen.

In another embodiment, unmanned vehicle 100 may provide cell phoneand/or satellite phone uplink and/or unmanned vehicle 100 could operateas a repeater to the same (and as such multiple unmanned vehicles 100may be daisy chained together to provide communication abilities).Another network feature that may be included is that vehicle 100 mayprovide network connectivity, such as cell phone tower (e.g., byimitating a cell phone tower) and/or a Wifi network.

In another embodiment, unmanned vehicle 100 may include video streamingfunctionality. For example, if a claim is initiated by or on behalf ofan insured (e.g., such as is described herein), an unmanned vehicle 100(be it aerial or grounded or a combination of both) may be deployed tothe insured and the insured may utilize unmanned vehicle 100 to performvideo and/or audio communications with provider 150 and/orrepresentatives associated therewith.

In another embodiment, unmanned vehicle 100 may provide a mobile ATMwhere currency distribution functionality has been (temporarily)disabled and/or undermined.

In another embodiment, unmanned vehicle 100 may be a parent unmannedvehicle 100 that has multiple child unmanned vehicles 100 that may dockwith and/or be partially or completely controlled by parent unmannedvehicle 100.

In another embodiment, a damage model, such as a tornado-damage model,may be utilized to determine which areas around a tornado's path shouldbe analyzed for possible damage, and therefore which areas to whichunmanned vehicle 100 should be deployed.

In another embodiment, unmanned vehicle 100 may detect that a property(e.g., a house) has been completely destroyed and initiate the claimsprocessing for that individual automatically, and/or unmanned vehicle100 may send an image and/or message related thereto to the insured sothat the insured can at least have the peace of mind of knowing theirproperty was damaged and/or destroyed (limited though said peace of mindmay well be).

In another embodiment, unmanned vehicle 100 may gather thermal imagery,which may be utilized to identify hail (or other) damage to a home'sroof.

In another embodiment, unmanned vehicle 100 may be utilized for frauddetection. For example, if an insured reports that the insured's car'sbumper has been fixed, one or more unmanned vehicles 100 may be sentand/or configured and/or requested to determine whether said repairactually was performed.

In another embodiment, data gathered from unmanned vehicle(s) 100 may beutilized to prevent and/or inform new policy enrollment decisions (e.g.,“you can't get fire insurance now because the forest fire is nextdoor”).

In another embodiment, data gathered from unmanned vehicle(s) 100 may beutilized to for targeted marketing of non-impacted homes (e.g., “yourneighbor had flood damage, so you should consider getting floodinsurance”).

In another embodiment, unmanned vehicle 100 could be deployed to aninsured and/or a prospective insured's location and/or house to conduct,obtain and/or retrieve the necessary medical tests and/or samples (suchas for enrollment, configuration, adjustment of health and/or lifeinsurance policies).

In another embodiment, unmanned vehicle 100 may be utilized to generatemodels that predict how much damage is expected around a certain rangeof an event. For example, a tornado with speeds of 85 mph, at 250 yardsthe damage is expected to be total destruction, up to 500 yards thedamage is moderate to heavy, etc.

In another embodiment, unmanned vehicle 100 may utilized monitor on-sitedamage to property (e.g., a corner of a building was damaged), detectthat vegetation needs to be watered, and/or take imagery of a gatheringsuch as a company party.

In another embodiment, a customer of an insurance company may sign upfor a service (which may or may not be a service the customer has to payfor), that includes the customer's associated provider 160 monitoringproperty identified by the customer. For example, the customer mayrequest an update from the provider if new data is gathered (e.g., newimages from unmanned vehicle 100). In another example, the customer mayrequest an update if analysis based on new data identifies one or morepredetermined situations (e.g., that the amount of flammable brushwithin a predetermined distance to the customer's home has exceeded athreshold). In another example, the customer may request the provider160 to monitor the customer's home because the customer is not home, inwhich case the customer may request that any detected changes result inan alert to the customer as well as a third party (e.g., the police).

In one exemplary use, the gathering phase of the process begins byreceiving requests from the interested consumers as to the type ofinformation desired (e.g., type of sensor data, acquisition frequency,area of interest, etc.). This information is used in the process step todetermine the necessary mission to satisfy the consumers. The prioritiesof the vehicle deployments are ranked based on the value attributed tothe mission. Deployments are coordinated with the governing entity andexecuted to collect the data. During the gathering phase the originalmission may be modified based on new inputs from customer's, or based onanalysis of the data conducted during the mission that indicates thecurrent or subsequent vehicle deployments can be altered to moreeffectively and efficiently complete the mission.

The storage phase consist of pre-processing data during the mission fora first layer of processed information either on the vehicle processorsor on other processors once the data has been transmitted from thevehicle. The location of the data storage can be accessed for uploadfrom the mission components. The customers can access the stored datavia application program interfaces. The data available to the individualcustomers is limited based on the policy previously defined for thecustomer.

The analysis phase can be conducted on the vehicle, or on otherprocessors. The analysis conducted on the data is defined by the inputsfrom the customers. Analysis provides more actionable data compared tothe raw data collected from the vehicle sensor. Since processing data onthe vehicle will likely be more expedient, the priority of the analysiscomputation location will depend on the priority which is defined duringthe gathering phase of the mission, but can be altered during themission based on new inputs from the customers. The fully processed datais stored with the raw data with access granted to customers based ontheir predefined policy. Sensitive data is compartmentalized for releaseonly to entities that have authorization to access the stored data.

The distribution phase is governed by the data requests that come fromthe consumers, and the priority given to those requests. The customer,commercial or public entity, with a predefined policy with the operatingentity requests the data via a communication channel of theirpreference. The interface between the customer and the stored data willbe harmonized via a standard interface protocol. The customers willreceive the requested data for their own use. The customers may alsoreceive notifications that the data they have requested is available fordownload, or other mean of consumption. The data disseminated cancontain digital tracking software so that policy of the consumer ismaintained and enforced for their data. Meaning, an organization willnot be able to further disseminate the data to alternate end-users notdefined in their policy. This will mitigate secondary ‘selling’ of dataor subsequent use of the data not previously agreed upon and enforceprivacy for private property that was the target of the acquisition.

FIG. 7A illustrates an exemplary overview of the step gathering(collecting) phase and the distribution step, among others. UAV 700 hasa real-time data uplink to a storage application programming interface(API) 703 within a data cloud 701. Storage API 703 stores data incommunicatively connected sensor database 702. Customer API 704retrieves data from sensor database 702, which may be the result of arequest of servers 706 of a customer. Other processes include detaileddata collection process 710, customer data notification process 720,flight planning process 730, customer data authentication and retrievalprocess 750, and determination of which entity to dispatch/fly 740. FIG.7B illustrates an exemplary detailed data collection process 710. UAV700 may include flight control CPU 712, data CPU 711, and sensor payload714. UAV 700 may be connected to a communications network, such asInternet 713. Data CPU 711 may include a sensor data analyzer (connectedwith a sensor payload), an upload manager, and a data link radio thatconnects with Internet 713.

FIG. 7C illustrates an exemplary flight planning process 730 anddetermination of which entity is dispatched process 740. Flight planningprocess 730 includes mission area variables defined 731 and real-timeanalysis preparation 732. Mission area variables defined 731 may includedefined gathering area, geo fencing/exclusions, obstetrical avoidancemetrics, altitude, and flight parameters. Real time analysis preparation732 includes gather client GEO info and estimate CPU capacity. Gatherclient GEO info may be connected customer geo access database 724 ofFIG. 7D. Real-time analysis preparation 732 connects with customer dataauthentication and retrieval process 750, which uploads details to UAV.Determination of which entity is dispatched process 740 includes thesteps of defining disaster area (741), registering dispatched entity(743), retrieving registered entity GEO information of interest (745),and entity chosen based on algorithmic result of the criteria entered(747). At block 745, retrieving registered entity GEO information ofinterest (745) may be from customer Geo Access database 724.

FIG. 7D illustrates an exemplary customer data notification process 720.Customer server 706 may provide legal rights to GEO specific data whichare affected by policies in place by geolocation (722). Approved GEOlocations may be stored in customer GEO access database 724. UAV 700uploads data to a sensor database 726. Customer API 721 may include APIauthentication. Also customer API 721 may receive notifications of GEOrelated data and sensor related data as well as provide notifications tocustomer server 706.

FIG. 7E illustrates an exemplary customer data authentication andretrieval process 750. Customer server 706 may request data from APIauthentication 751. API authentication is connected with or associatedwith API authentication of FIG. 7D. API authentication 721 may checkrights with customer GEO access database 724, which may send a messageto authorize release of data to sensor database 726. Sensor database 726may provide requested data to API authentication 751 and ultimatelycustomer server 706.

FIG. 8 illustrates an exemplary aspect of the gathering, storing, andmission modification process. At step 801, a claim incident occurs. Atstep 803, approval is obtained to operate unmanned aerial surveillance(UAS), which may be from a local or federal authority (805). At step807, there is an operation of an initial mission and pre-processing ofactionable information, which may include CAT geographic boundaries(809). At step 813, there may be in-flight UV intelligence to determinealternative payloads/flight paths needed. At step 815, there alternativeUV, payload, and flight or ground plan may be executed, which may bebased on client requested imagery or sensor data. At step 819, there isa determination of whether acquired imagery is comprehensive for all endusers. If yes, then end UAS mission and begin data processing anddissemination to end users (823). If no, then go back to step 813. Step811 provides for uploading data to a cloud, such as data related to step807 or step 815. The uploaded data of step 811 may also be subsequentlyuploaded to step 823 with regard to processing and dissemination to endusers after ending a UAS mission.

With continued reference to FIG. 8, described herein are systems andmethods for facilitating claims processing, such as by utilizingunmanned vehicles. In one aspect, unmanned aerial surveillance (UAS),such as an unmanned aerial vehicle, is utilized to gather data relatedto one or more insurance claims. The UAS may be sent on a mission togather data over an area that has recently been subject to an event thatcaused widespread damage (e.g., hurricane). The UAS may process the datainternally before forwarding the data to a central server, and the datamay be forwarded during the mission, and/or after the mission iscomplete. The data from the UAS may be shared between multiple entitiesand utilized to initiate and/or accelerate processing of claims againstinsurance policies. UAV on-board intelligence determines if othersystems are necessary to more thoroughly assess types of damage in thereturn on investment (ROI). On-board intelligence can be augmented withdecision made by clients reviewing the uploaded imagery or sensor data.Certain payloads are better suited to acquire actionable information ifthe damage was a result of rain, wind, storm surge, fire, etc. CertainUVs (e.g, aerial VTOL, aerial fixed wing, terrestrial, by-modal) arebetter suited to access and image damage based on location,accessibility, and other hazards.

Although at least one embodiment in FIG. 2 depicts that an unmannedvehicle 100 that is vehicle 110, is it contemplated herein that anyvehicle may be deployed and/or utilized in such a way as to practice oneor more elements, systems, and/or methodologies as described herein.

Referring to FIG. 4, illustrated therein is an exemplary embodiment of acomputing device as might be used when utilizing the systems and methodsdescribed herein. In one embodiment, computing device 300 includesmemory 310, a processor 302, an interface device 304 (e.g., mouse,keyboard, monitor), a network device 306. Memory 310 in one examplecomprises a computer-readable signal-bearing medium. One example of acomputer-readable signal-bearing medium comprises a recordable datastorage medium, such as a magnetic, optical, biological, and/or atomicdata storage medium. In another example, a computer-readablesignal-bearing medium comprises a modulated carrier signal transmittedover a network coupled with system 90, for instance, a telephonenetwork, a local area network (“LAN”), the Internet, and/or a wirelessnetwork. In one example, memory 310 includes a series of computerinstructions written in or implemented with any of a number ofprogramming languages, as will be appreciated by those skilled in theart.

Memory 310 in one example includes RAM 312, hard drive 315, which mayinclude database 316. Database 316 in one example holds information,such as information that relates to users and/or parties interactingwith system 90. Further, database 316 may reside at a location otherthan on server 150.

The terms “engine” and “module” denote a functional operation that maybe embodied either as a stand-alone component or as an integratedconfiguration of a plurality of subordinate components. Thus, enginesand modules may be implemented as a single engine/module or as aplurality of engine/modules that operate in cooperation with oneanother. Moreover, engines/modules may be implemented as softwareinstructions in memory 310 or separately in any of hardware (e.g.,electronic circuitry), firmware, software, or a combination thereof. Inone embodiment, engines/modules contain instructions for controllingprocessor 302 to execute the methods described herein. Examples of thesemethods are explained in further detail in the subsequent of exemplaryembodiments section-below.

The techniques described herein are exemplary, and should not beconstrued as implying any particular limitation on the presentdisclosure. It should be understood that various alternatives,combinations and modifications could be devised by those skilled in theart. For example, steps associated with the processes described hereincan be performed in any order, unless otherwise specified or dictated bythe steps themselves. The present disclosure is intended to embrace allsuch alternatives, modifications and variances that fall within thescope of the appended claims.

The terms “comprises or “comprising” are to be interpreted as specifyingthe presence of the stated features, integers, steps or components, butnot precluding the presence of one or more other features, integers,steps or components or groups thereof.

Although the systems and methods of the subject invention have beendescribed with respect to the embodiments disclosed above, those skilledin the art will readily appreciate that changes and modifications may bemade thereto without departing from the spirit and scope of the subjectinvention.

What is claimed is:
 1. A computerized method of managing vehicledeployment and operations, the method comprising: identifying at leastone property about which to gather information; deploying a vehicle to alocation associated with the at least one property; gathering data, bythe deployed vehicle; determining a portion of the gathered dataassociated with the at least one property; and encrypting the determinedportion of the gathered data.
 2. The method of claim 1, the methodfurther comprising identifying a company related to the at least oneproperty; and wherein the encrypting the determined portion of thegathered data comprises encrypting the determined portion using anencryption key associated with the company.
 3. The method of claim 1,wherein the vehicle comprises an unmanned vehicle with flyingcapabilities.
 4. The method of claim 1, the method further comprising:receiving, from the vehicle, imagery associated with a navigation of thevehicle to the location associated with the at least one property; anddetermining a navigational path based on the imagery.
 5. The method ofclaim 4, wherein the gathering data comprises: capturing a first imageof the at least one property; and receiving a second image of the atleast one property, wherein the second image was captured before thefirst image was captured; and the method further comprising comparingthe first and second image to: identify a structure in the first image;and identify a part of the structure in the second image, whereinidentifying the part of the structure in the second image is based atleast in part on identifying the structure in the first image.
 6. Themethod of claim 1, wherein the gathering data comprises capturing afirst image of the at least one property; and the method furthercomprising analyzing the first image to determine that a supplementalimage should be gathered.
 7. The method of claim 6, the method furthercomprising, based on determining that the supplemental image should begathered, sending a request, from the vehicle to a second vehicle, togather the supplemental image.
 8. The method of claim 1, wherein thegathering data comprises capturing a first image of the at least oneproperty; and the method further comprising: identifying an amount ofavailable data storage space on the vehicle; and deleting the firstimage without saving it based on the amount of vehicle's available datastorage space being less than a predetermined threshold.
 9. The methodof claim 8, wherein the amount of available data storage space is basedat least in part on an amount of available data storage space allocatedfor a company associated with the at least one property.
 10. The methodof claim 1, wherein the gathering data comprises capturing a first imageof the at least one property; and the method further comprising:identifying an amount of available communication bandwidth; and based onthe amount of vehicle's data storage space being less than apredetermined threshold, deleting the first image without the vehiclecommunicating the first image.
 11. The method of claim 10, wherein theamount of available communication bandwidth is based at least in part onan amount of available communication bandwidth allocated for a companyassociated with the at least one property.
 12. The method of claim 1,the method further comprising transmitting, by the vehicle and to anaccess device associated with the at least one property, an access code,wherein the access device is configured to enable access to a structureon the at least one property based on receiving the access code.
 13. Themethod of claim 1, the method further comprising transmitting, based onthe gathered data and to a computing device associated with the at leastone property, an indication of a gas leak associated with the at leastone property.
 14. The method of claim 1, the method further comprisingreceiving an indication of a heat distribution for the at least oneproperty structure.
 15. The method of claim 14, the method furthercomprising in response to the receiving the indication of the heatdistribution, capturing a thermal scan of the structure.
 16. The methodof claim 1, wherein the data comprises image data; and wherein thedetermining the portion of the gathered data associated with the atleast one property comprises determining a portion of the image datacomprising an image of the at least one property.
 17. The method ofclaim 1, the method further comprising storing the determined portion ofthe gathered data to a first storage location and another portion of thegathered data to a second storage location different than the firststorage location.
 18. The method of claim 1, wherein the determining theportion of the gathered data associated with the at least one propertycomprises comparing the gathered data to data gathered at an earliertime.
 19. A computerized method of managing vehicle deployment andoperations, the method comprising: identifying at least one propertyabout which to gather information; deploying a vehicle to a locationassociated with the at least one property; requesting, by the vehicleand from a computing device that manages, at least in part, a structureon the at least one property, access to the structure; responsive tobeing allowed access to the structure, gathering data associated withthe at least one property; determining a portion of the gathered dataassociated with the structure; and storing the determined portion of thegathered data at a first storage location and another portion of thegathered data at a second storage location different than the firststorage location.
 20. The method of claim 19, the method furthercomprising receiving a communication from the computing device thatincludes information describing a heat distribution for the structure.21. The method of claim 20, the method further comprising, in responseto the receiving the communication describing the heat distribution forthe structure, the vehicle capturing a thermal scan of the structure.22. The method of claim 19, the method further comprising encrypting thedetermined portion of the gathered data, wherein the another portion ofthe gathered data is not encrypted; and wherein the storing thedetermined portion of the gathered data at the first storage locationcomprises storing the encrypted determined portion of the gathered dataat the first storage location.
 23. A computerized method of managingvehicle deployment and operations, the method comprising: identifying atleast one property about which to gather information; deploying avehicle to a location associated with the at least one property;gathering data, by the deployed vehicle; determining a portion of thegathered data associated with the at least one property; and storing thedetermined portion in a first storage location and another portion ofthe gathered data in a second storage location different from the firststorage location.